DAGparameters: Augment a DAG with parameters

In Bestie: Bayesian Estimation of Intervention Effects

Augment a DAG with parameters

Description

DAGparameters takes a DAG and augments it with parameters. For binary data these are the parameters of the posterior beta distributions and its mean. For continuous data, these are parameters of the posterior distributions of the edge coefficients from arXiv:2010.00684. There is support for user-defined augmentation, with the caveat that it must match the output format of either the binary or continuous cases.

Usage

DAGparameters(incidence, dataParams, unrollDBN = TRUE)

Arguments

incidence	a single adjacency matrix with entry [i,j] equal to 1 when a directed edge exists from node i to node j
dataParams	the data and parameters used to learn the DAGs derived from the scoreparameters function of the BiDAG package
unrollDBN	logical indicating whether to unroll a DBN to a full DAG over all time slices (TRUE, default) or to use the compact representation (FALSE)

Value

the DAG and a list of parameters for each node given its parents

Examples

scoreParam <- BiDAG::scoreparameters("bde", BiDAG::Asia)
AsiaParam <- DAGparameters(BiDAG::Asiamat, scoreParam)

Bestie documentation built on April 28, 2022, 5:06 p.m.